Data interoperability is vital to today’s healthcare computing environment, allowing clinical information to be effectively and consistently exchanged, compared, and analyzed among healthcare partners such as insurers, pharmacies, affiliated providers, and public health departments. Put simply, data interoperability enables better decision making.
"Time is money". That old saying is as relevant as ever in the modern financial service markets. Complex, real-time, and algorithmic trading are constantly pushing the envelope of that phase.
The way SOA implementations are being implemented today, there's a new demand for middleware component that provides necessary services such as high-speed message level parsing, validation, transformation and translation to different message formats, message-level routing, service management, governance and control. Intel’s high-performance software solution is uniquely positioned to offer variety of such services critical in implementing true SOA.
This is the third of a three-part article looking at the area of interoperability and health information exchange (HIE) in the healthcare industry. In the first part, I intended to clearly articulate the key challenges and barriers to adoption faced by those looking to engage in HIE.
This is the second of a three-part article looking at the area of interoperability and health information exchange (HIE) in the healthcare industry. In the first part, I intended to clearly articulate the key challenges and barriers to adoption faced by those looking to engage in HIE. Part 2 will examine an architectural approach to address those challenges and discuss some technology enablers to realize a vision for high quality HIE.
Earlier I computed various statistical estimates like mean or variance-covariance matrix using Intel® Summary Statistics Library. In those cases I knew for sure that my datasets did not contain “bad” observations (points which do not belong to the distribution which I observed) or outliers. However, in some cases we need to deal with datasets which are contaminated with outliers.
In many conversations I participate in regarding Service Oriented Architecture (SOA), part of the conversation oftens leads to "....how best can I incorporate my mainframe in the SOA architecture...". There are a number of mainframe SOA-enabling options, and in this post I will share my opinion on the application of a short-list of tried and true approaches.
Integrating the hot, new SaaS application into a company can often be a challenging undertaking. The SaaS application was acquired for a pressing departmental need, yet manually re-inputting and syncing key data like employee, vendor or supplier master directories is not practical. Manually coordinating a sale by the customer saying "yes" with a win recorded in the sales force automation tool yet hand crafting delivery instructions in the order module of the ERP is not really a sustainable business proc